Candidates will receive a printed resource booklet to support their answers.
Candidates will be required to respond in short and /or extended answers (800–1500 words in total) to questions relating to their choice of ONE of the following areas of computer science:
complexity and tractability
computer vision
computer graphics
For computer vision, questions may cover:
noise
thresholding
edge detection
image processing for computer vision
applications in fields of obstacle detection (e.g. Lidar and stereo vision)
feature extraction (e.g. Viola Jones, Haar-like features)
medical detection, and the application of techniques to medical diagnosis (e.g. convolutional neural networks, decision trees, and random forests).
Teachers are encouraged to help their students to develop answering techniques to ensure that they are able to respond clearly and concisely within the total recommended word limit.
Responses that exceed this may not be considered for assessment past the 1500-word limit.
Teachers are strongly encouraged to prepare students to be able to apply their understanding of computer science to unfamiliar contexts.
Teachers should prepare students to identify and articulate instances where overlap with various areas of computer science occurs, e.g. with artificial intelligence.
the key aspects of the computer science area
relevant algorithms or other mechanisms behind the area
how the area is used, is implemented, or occurs, giving examples.
Students use information including research and/or classwork that they have previously undertaken within a computer science area in the achievement standard. They use this information to support their statements about the key aspects, how the area is implemented and to provide reasoning for the behaviour of the algorithms or mechanisms used within their context. For example (within computer vision), how an algorithm can pick up and identify facial features.
Students will provide a detailed account of how and why a computer science area occurs, within a particular context. For example (within computer vision): detailing why and how facial recognition is used by computers to match a facial scan to the photograph embedded in an e-passport.
Students use information from research and/or classwork within the chosen computer science area to:
provide a detailed explanation of how the technical capabilities and limitations of the area relate to humans, giving examples
compare and contrast different perspectives on the area.
Students analyse, with examples, the capabilities and limitations of the chosen computer science area and with humans. Students break an issue into its constituent parts and look in depth at each part using supporting arguments and evidence on how perspectives for and against and how these are interrelated to one another.
drew accurate conclusions linked to their earlier responses
argued why their conclusions were valid, true, applicable or correct
drew conclusions that showed the candidate comprehensively understood the area they were discussing
criticised the area objectively
linked their insightful conclusions to their previous answers rather than postulating new technologies, or knowledges, or outcomes, without providing a premise for a train of reasoning.